Conference Paper

Evaluation of Approaches for Tracking Virus Particles in Fluorescence Microscopy Images.

Conference: Bildverarbeitung für die Medizin 2009: Algorithmen - Systeme - Anwendungen, Proceedings des Workshops vom 22. bis 25. März 2009 in Heidelberg
Source: DBLP
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    ABSTRACT: The lateral mobility of lipids in phospholipid membranes has attracted numerous experimental and theoretical studies, inspired by the model of Singer and Nicholson (1972. Science, 175:720-731) and the theoretical description by Saffman and Delbrück (1975. Proc. Natl. Acad. Sci. USA. 72:3111-3113). Fluorescence recovery after photobleaching (FRAP) is used as the standard experimental technique for the study of lateral mobility, yielding an ensemble-averaged diffusion constant. Single-particle tracking (SPT) and the recently developed single-molecule imaging techniques now give access to data on individual displacements of molecules, which can be used for characterization of the mobility in a membrane. Here we present a new type of analysis for tracking data by making use of the probability distribution of square displacements. The potential of this new type of analysis is shown for single-molecule imaging, which was employed to follow the motion of individual fluorescence-labeled lipids in two systems: a fluid-supported phospholipid membrane and a solid polymerstabilized phospholipid monolayer. In the fluid membrane, a high-mobility component characterized by a diffusion constant of 4.4 microns2/s and a low-mobility component characterized by a diffusion constant of 0.07 micron2/s were identified. It is proposed that the latter characterizes the so-called immobile fraction often found in FRAP experiments. In the polymer-stabilized system, diffusion restricted to corrals of 140 nm was directly visualized. Both examples show the potentials of such detailed analysis in combination with single-molecule techniques: with minimal interference with the native structure, inhomogeneities of membrane mobility can be resolved with a spatial resolution of 100 nm, well below the diffraction limit.
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    ABSTRACT: This paper presents a computationally efficient, two-dimensional, feature point tracking algorithm for the automated detection and quantitative analysis of particle trajectories as recorded by video imaging in cell biology. The tracking process requires no a priori mathematical modeling of the motion, it is self-initializing, it discriminates spurious detections, and it can handle temporary occlusion as well as particle appearance and disappearance from the image region. The efficiency of the algorithm is validated on synthetic video data where it is compared to existing methods and its accuracy and precision are assessed for a wide range of signal-to-noise ratios. The algorithm is well suited for video imaging in cell biology relying on low-intensity fluorescence microscopy. Its applicability is demonstrated in three case studies involving transport of low-density lipoproteins in endosomes, motion of fluorescently labeled Adenovirus-2 particles along microtubules, and tracking of quantum dots on the plasma membrane of live cells. The present automated tracking process enables the quantification of dispersive processes in cell biology using techniques such as moment scaling spectra.
    Journal of Structural Biology 09/2005; 151(2):182-95. DOI:10.1016/j.jsb.2005.06.002 · 3.37 Impact Factor
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    ABSTRACT: Fluorescence time-lapse microscopy is a powerful technique for observing the spatial-temporal behavior of viruses. To quantitatively analyze the exhibited dynamical relationships, tracking of viruses over time is required. We have developed probabilistic approaches based on particle filters for tracking multiple virus particles in time-lapse fluorescence microscopy images. We employ a mixture of particle filters as well as independent particle filters. For the latter, we have developed a penalization strategy to maintain the identity of the tracked objects in cases where objects are in close proximity. We have also extended the approaches for tracking in multi-channel microscopy image sequences. The approaches have been evaluated based on synthetic images and the performance has been quantified. We have also successfully applied the approaches to real microscopy images of HIV-1 particles and have compared the tracking results with ground truth from manual tracking.
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